The anticipation of widespread use of electric automobiles has caused many researchers and manufacturers to consider the demands for battery charging under a variety of different circumstances. These considerations have led to a variety of innovations that relate to various aspects of the problem. For example, one aspect of the widespread use of electric automobiles is the need to charge different types of batteries at commercial charging stations. To accommodate the different types of batteries, these commercial charging stations will need to have the capability to interact with the battery and analyze any considerations related to the battery type before applying a charge safely. Another consideration brought forth by the widespread use of electric cars relates to the likelihood that many of these electric cars will be charged in the homes of the users, utilizing electrical power produced by public and private electrical power producers. The supply, demand, and cost of electrical power supplied to these homes will vary over time. To accommodate that variance, the battery charging connections set up in the homes of these users will optimally determine a charging time and/or rate for the battery that best suites the needs of these public and private electrical power producers.
But it is not battery type alone that will create constraints on the charging process. Because electric vehicles are mobile, one cannot predict every permutation of battery, battery charger, charging station, and energy service provider that might become encountered as an electric vehicle travels about and charges its batteries at various homes, workplaces, and at public charging locations. Therefore, a method is needed to recognize and accommodate the numerous constraints that might be imposed by each battery type, battery charger, charging station and energy service provider.
While many innovations have been proposed to accommodate the various charging constraints and charging preferences posed by widespread charging of electric automobiles, the prior art has generally considered these various constraints and preferences in isolation. While many of these prior solutions and innovations are suitable when considering charging constraints and preferences in isolation, these prior innovations do not provide a solution that is optimal when the various constraints and preferences of all of the users and all devices connected to the battery are considered. Thus, there exists a need for methods and apparatus for charging batteries that is capable of considering the constraints and preferences of a wide variety of users and devices that impact, or are impacted by, the charging process. The present invention satisfies that need.